ArticleBioinformatics (Oxford, England)2017
Exploring spatially adjacent TFBS-clustered regions with Hi-C data.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 2 citations in OpenAlex.
- The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model.Nucleic acids research · 2024Article
- Regulatory patterns analysis of transcription factor binding site clustered regions and identification of key genes in endometrial cancer.Computational and structural biotechnology journal · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
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Abstract
motivationTranscription factor binding sites (TFBSs) are clustered in the human genome, forming the TFBS-clustered regions that regulate gene transcription, which requires dynamic chromatin configurations between promoters and distal regulatory elements. Here, we propose a regulatory model called spatially adjacent TFBS-clustered regions (SATs), in which TFBS-clustered regions are connected by spatial proximity as identified by high-resolution Hi-C data.
resultsTFBS-clustered regions forming SATs appeared less frequently in gene promoters than did isolated TFBS-clustered regions, whereas SATs as a whole appeared more frequently. These observations indicate that multiple distal TFBS-clustered regions combined to form SATs to regulate genes. Further examination confirmed that a substantial portion of genes regulated by SATs were located between the paired TFBS-clustered regions instead of the downstream. We reconstructed the chromosomal conformation of the H1 human embryonic stem cell line using the ShRec3D algorithm and proposed the SAT regulatory model. CONTACT: ylu.phd@gmail.com or boxc@bmi.ac.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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